Evaluation of Advanced Practice Radiation Therapist integration in an inpatient palliative radiation therapy service: a single-center prospective observational mixed-methods study

Introduction

The Mount Sinai Hospital department of Radiation Oncology, staffed by attending physicians and house staff, operates a high-volume palliative radiation therapy (PRT) program serving both inpatient and outpatient populations. To address rising inpatient demand for urgent PRT, the department introduced an Advanced Practice Radiation Therapist (APRT) to enhance workflow and coordination, supported by prior published data (1). APRTs are radiation therapists with advanced clinical training who provide quality improvement (QI)-driven care and support physician practice while under their supervision, distinct from nurse practitioners and physician assistants (2-4). Internationally, APRT models structured around the four pillars of advanced practice-clinical care, education, leadership, and research have demonstrated improvements in continuity, decision-making, and care quality (5). Nationally, APRT models are being adapted to institutional needs, emerging in palliative, adaptive therapy, and rural settings, laying the groundwork for a sustainable advanced level of practice to strengthen care delivery (1-6).

This study summarizes early findings from a single-center mixed-methods study evaluating associations between APRT integration and clinician-reported burnout, satisfaction, and key performance indicators (KPIs). In this advanced-level care model, the APRT possesses specialized knowledge of radiation oncology procedures and palliative care enabling them to manage time-sensitive tasks such as simulation coordination, patient education/preparation, and management of interdepartmental workflows and communication (2,5,6). The objective of this study was to explore associations between APRT integration and (I) clinician well-being, and (II) key departmental performance indicators within an inpatient PRT service.

Background and significance

Clinician burnout is a persistent concern in radiation oncology, with national surveys reporting rates of 40% to 55% among faculty and residents (7-9). Common contributors include high clinical volume, documentation burden, and limited time for patient-facing care (7). At this institution, a 2019 faculty well-being survey revealed that while all radiation oncologists (ROs) found their work to be meaningful, fewer than half felt adequately supported, and many reported extensive after-hours documentation within the electronic medical record (EMR).

Caring for patients requiring PRT further amplifies these pressures, particularly when PRT is indicated urgently during an inpatient stay. Urgent or emergent inpatient PRT compresses treatment planning into hours, requiring rapid coordination between inpatient teams, physicists, and therapists. In this current setting, Epic is the hospital’s system wide EMR used for inpatient documentation, orders, and transport coordination, whereas Mosaiq is the radiation oncology record-and-verify system used for scheduling, radiation therapy (RT) documentation and treatment delivery operations. Because these systems function independently and share information through interface, real-time scheduling and inpatient information can involve manual communication and duplication of tasks. Clearance of inpatients from the frontline provider for daily treatment and completion of clinical care notes can add to inefficiencies of clinician burden. The complexity of care was further supported by our local QI review: in 2021, departmental QI data showed that more than 60% of unfinished PRT courses were inpatient cases, underscoring the need for a targeted workflow intervention (10). Advanced practice models have been shown to improve coordination, sustainability, and care quality in similar high-complexity services (11-13). APRTs are radiation therapists with advanced clinical and technical competencies who function under physician supervision within a well-defined institutional scope (2-6). Internationally, APRT integration has been associated with enhanced continuity, quality assurance (QA), and team-based care in palliative and adaptive radiotherapy programs (14-19).

Given the pre-implementation burden and coordination demands of inpatient PRT, our department piloted a full-time APRT embedded within the inpatient PRT service to support time-sensitive, non-billable patient care tasks and coordination. The role focused on patients completing throughput steps such as simulation eligibility, treatment initiation, and treatment completion of the prescribed full course. Utilizing an APRT patient assessment and interdepartmental coordination the role aims to streamline communication and support continuity of care across consultation, simulation, and treatment. In this institution, the APRT role helped close communication gaps and monitor important departmental QI/QA KPIs such as inpatient clearance by the frontline provider in Epic to ensure safe patient arrival to the RO department and documentation compliance of clinical care notes. We present this article in accordance with the STROBE reporting checklist (available at https://apm.amegroups.com/article/view/10.21037/apm-2025-1-144/rc).

Methods

The single-center mixed-methods prospective observational study aimed to explore whether APRT integration is correlated with improvements in care coordination through KPIs, communication, and clinician workload burden. Specifically, we hypothesized that embedding an APRT within the PRT service would support completion of non-billable, time-sensitive, and often burdensome care coordination tasks and that this would in turn correspond with reduced burnout among clinicians and improve operational performance. The study was conducted at the Mount Sinai Hospital, where APRT integration began in September 2022, and data were collected prospectively from May 2023 to November 2024 at 6-month intervals. The attending and residents providing inpatient clinical coverage were eligible to participate in the survey. Eligible participants were prespecified as the 13 attending ROs and 10 resident trainees who were part of the inpatient palliative RT service during the study period. This clinician group remained consistent across the 24-month evaluation, and all were exposed to the APRT-supported inpatient workflow. Surveys were emailed at four intervals, and participation was voluntary and anonymous. Because the survey did not collect identifiers, individual-level response rates could not be calculated, and reasons for non-participation could not be determined. Duplicate submissions were screened at each timepoint; when duplicates were identified, only the first complete submission was retained for analysis. Missing demographic values were retained as missing and not imputed. As this was a prospective study conducted at a single center, the sample size was determined by the number of clinicians who elected to complete the survey at each interval. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This project received approval from the Icahn School of Medicine Institutional Review Board (No. STUDY-23-00265). Before accessing the survey, all participants were informed of this study.

Statistical analysis

Data were collected at 6-, 12-, 18-, and 24-month post-integration. Clinician well-being was assessed using the validated American Medical Association (AMA) Mini-Z 2.0 survey, which evaluates burnout, perceived stress, job satisfaction, and workplace factors such as workload, EMR burden, and leadership support (20,21). In this study, EMR refers to the overall electronic documentation burden captured by the AMA Mini-Z instrument and was not system-specific; respondents may have interpreted this as reflecting documentation across both Epic and Mosaiq used in their workflow. The AMA Mini-Z 2.0 was selected because it was recommended by our institution’s Office of Well-Being and Resilience as part of this internally funded research. Two open-ended questions were included to capture physicians’ perspectives on APRT integration: (I) in the past six months, did you have the opportunity to work with the APRT? If yes, what aspects of the integration worked well? (II) if yes, what aspects did not work well or could be improved? Survey quantitative results, free-text responses, and departmental KPIs were analyzed separately and then interpreted together by aligning each survey wave with the same KPI reporting window and comparing trends over time. Operational performance was assessed using routinely reported departmental QI/QA monthly metrics. In this study, operational performance refers to department-level KPIs that track readiness, throughput, and follow-through in the inpatient PRT workflow. KPI definitions were specified a priori, aligned to our prior inpatient throughput work, and included simulation eligibility [physician ordered computed tomography (CT) simulation], simulation completion (simulation completed in one session), treatment initiation (verification of the first planned fraction), completion of the prescribed course (all intended fractions delivered as ordered), and documentation compliance (per departmental QI/QA criteria). Because this was an observational study without a control group, changes in AMA Mini-Z responses may also reflect other contemporaneous workplace factors; results are therefore interpreted associative. Surveys were administered online using REDCap and distributed by email with a secure survey link at each interval. Responses were submitted directly in REDCap (not by email), collected anonymously without identifiers, and the distribution list was maintained separately from survey response data.

The APRT intervention

The APRT practices under the supervision of the department’s ROs, who provide care to palliative inpatients referred for RT on a continual basis (2). The role was developed as a key provider within the broader multidisciplinary team (MDT), with the APRT seeing inpatients while hospitalized, before simulation and treatment planning, and during treatment when needed. With over 20 years of experience as a practicing radiation therapist and prior responsibility for day-to-day departmental operations, the APRT brought practical insight into inpatient safety and workflow barriers and supported stakeholder engagement during implementation. Using a structured assessment and coordination workflow, the APRT focused on time-sensitive, non-billable tasks and facilitated timely communication with the attending physician or house staff regarding patient-readiness factors, evolving inpatient status, and logistical barriers that can delay simulation or disrupt treatment initiation. The APRT does not enter billable notes, perform simulations, review or approve treatment imaging, determine clinical decision-making or goals of care, or oversee departmental operations or staff management, the role functions within defined clinical guardrails. Physician and resident responsibilities for billable tasks (e.g., consultation documentation, orders, imaging approval, contouring/planning, and isocenter placement) were unchanged. Because inpatient acuity often requires complex workups and competing clinical priorities, simulation and treatment of eligibility/completion outcomes should be interpreted as operational service-level KPIs. In addition, the APRT completed a Master of Science in Advanced Clinical Practice in Radiation Oncology at Sheffield Hallam University, which provided training in service design and a broader, global perspective on the development and implementation of workflow change beyond a single department. The APRT role reporting structure is shown in Figure 1.

Figure 1 APRT role placement within the inpatient palliative radiation therapy service: organizational and communication pathways. The dotted line indicates the APRT’s clinical collaboration with attending radiation oncologists. APRT, Advanced Practice Radiation Therapist; VP, vice president.

Quantitative analysis

A total of 23 clinicians were eligible for the survey, including 13 ROs and 10 residents. At 6 months, 11 responded [48% overall; 9 ROs (69%), 2 residents (20%)]. At 12 months, 17 responded [74% overall; 13 ROs (100%), 4 residents (40%)]. At 18 months, 18 responded [78% overall; 13 ROs (100%), 6 residents (60%)]. At 24 months, 12 responded [52% overall; 10 ROs (77%), 2 residents (20%)]. Burnout was defined as scores ≥3 on the validated AMA Mini-Z burnout item (20). Responses were summarized using descriptive statistics, and missing data were handled with available-case analysis at each time-point. Because the survey was anonymous and responses could not be linked across time points, each follow-up represents an independent cross-sectional sample rather than a longitudinal cohort. Temporal trends in proportions with available data were assessed using the Cochran-Armitage trend test, which is appropriate for evaluating trends in binary outcomes across ordered groups (i.e., sequential time points). The association between burnout and workplace factors was evaluated using Spearman correlation coefficients.

Simulation eligibility was defined a priori, consistent with our prior inpatient throughput study (2), as physician clinical clearance/readiness to proceed to CT simulation within the departmental presimulation clearance workflow, rather than a fixed patient characteristic. Physician clearance reflects completion/verification of key readiness elements (e.g., consent status, required documentation/workup completion, relevant imaging availability, and readiness to tolerate simulation positioning and transport). Simulation completion was defined as a patient who began and completed their simulation appointment within one setting. Treatment initiation was defined as verification of the first planned fraction. Completion of the prescribed course was defined as delivery of all intended fractions as prescribed. Documentation compliance was assessed using departmental QI/QA definitions from the same reporting workflow. Two-proportion z-tests compared post-integration outcomes to baseline (0–6 months). Communication safety entries were collected from the health system risk management system (SafetyNet) and summarized descriptively. All analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, NC), with P<0.05 considered statistically significant. All estimates are unadjusted because the study design did not support multivariable modeling.

Qualitative analysis

Open-ended responses were collected in REDCap at each survey interval (6, 12, 18, and 24 months). In addition to the APRT integration prompts (“If yes, what went well?” and “If yes, what did not go well?”), the survey included an AMA Mini-Z free-text item (“Tell us more about work-related stresses and what we can do to minimize them.”) and two additional items to assess inpatient workflow burden over the prior 6 months (daily after-hours patient-care work and common inpatient work interruptions). Open-text completion for the analyzed fields was high across survey waves (94.7–100% of respondents per interval), indicating the qualitative dataset reflected input from nearly all respondents at each time point. Because responses were brief, we used an inductive qualitative content analysis approach (22,23). The study principal investigator (PI) and co-principal investigator (co-PI) conducted the analysis; neither served as the APRT nor was a clinician survey respondent. Reviewers independently read responses, generated initial codes, and iteratively refined a study-specific codebook with definitions and exemplar quotes, then applied codes across all survey waves and grouped them into higher-order content categories. Where category frequencies are reported, they are descriptive (proportion of respondents whose comments reflected each category by wave), and respondents could contribute to multiple categories.

Results

Clinician-reported burnout decreased over the follow-up period among respondents (Figure 2). A decreasing trend was observed over time (P=0.008); however, given the modest and varying response rates across timepoints and the anonymous repeated cross-sectional design, this finding should be interpreted cautiously as exploratory and hypothesis-generating. In the stratified analysis by the professional roles, residents reported no burnout at any post-intervention time-points, whereas the observed decline in burnout over time was driven primarily by ROs (Table S1). Although the proportion of respondents reporting stress varied across survey distributions, there were no statistically significant temporal changes in perceived stress (P=0.39) or job satisfaction (P=0.48). The proportion of respondents reporting stress ranged from 17.6% to 58.3% across time points; proportions should be interpreted relative to the modest sample size shown in Figure 2. Perceptions of a highly supportive practice environment increased over time (P=0.03), whereas other AMA Mini-Z subscales, including workplace joy and manageable EMR pace, did not demonstrate significant trends (P>0.05), as shown in Figure 3. EMR-related burden showed consistent positive correlations with burnout at 6, and 24 months (P=0.001 and P=0.008, respectively). The AMA Mini-Z EMR items capture overall electronic documentation burden and pace and are not platform-specific; therefore, responses may reflect clinicians’ combined experience across Epic and Mosaiq. At 12 months, burnout was most strongly associated with documentation time: higher burnout correlated with less perceived time for documentation (Spearman ρ=−0.73, P<0.001). At 18 months, burnout remained strongly and significantly associated with multiple workplace drivers, including lower team efficiency (Spearman ρ=−0.73, P<0.001), less control over workload (ρ=−0.67, P=0.002), and a more hectic pace of work (Spearman ρ=−0.58, P=0.009). Figure 4A-4D presents the correlation matrices at each interval and demonstrates stable inverse associations between burnout and indicators of team efficiency and alignment with clinical leadership. Descriptively, temporary fluctuations in workload control and team coordination were observed following APRT integration, although after-hours EMR documentation remained consistently identified as a strain on the clinicians.

Figure 2 Bar chart illustrating proportion of participants reporting burnout, job satisfaction and stress over time.

Figure 3 Bar chart illustrating trends in Mini-Z survey overall and subscales. EMR, electronic medical record.

Figure 4 Correlation heat maps of Mini-Z worklife domains and burnout across follow-up intervals (Spearman ρ). (A) Six months post-integration: burnout was most strongly associated with documentation burden, including insufficient time for documentation and after-hours EMR work. (B) Twelve months post-integration: burnout remained most strongly associated with documentation time, with additional moderate associations with workload control and team efficiency. (C) Eighteen months post-integration: burnout was most strongly associated with team efficiency and control over workload, with additional associations with work pace and values aligned with clinical leadership. (D) Twenty-four months post-integration: burnout was most strongly associated with time spent on the EMR at home, with a moderate association with workload control; team-level domains remained interrelated. *, statistically significant Spearman correlation at P<0.05. EMR, electronic medical record; Mini-Z, Mini-Z 2.0 survey; ρ, Spearman correlation coefficient.

Quantitative analysis of departmental QI and QA metrics demonstrated statistically significant changes across several operational outcomes over the 24 months as seen in Table 1. Simulation eligibility increased from 49.4% at baseline to 76.2% at 18–24 months (P<0.001). Simulation completion among eligible patients rose from 83.2% at baseline to 95.1% at 18–24 months (P=0.001). Completion of treatment initiation remained consistent, with no significant differences between baseline (91.9%) and 18–24 months (92.7%; P=0.80). The authors acknowledge that treatment completion was already high at baseline and remained stable over time, leaving limited opportunity to demonstrate measurable improvement in this endpoint. Completion of the entire prescribed course increased from 82.4% at baseline to 93.7% at 18–24 months (P=0.004). To contextualize the simulation completion metric, a targeted chart review was performed for cases in which eligible patients did not complete or postponed simulation. An additional Icahn School of Medicine Institutional Review Board approval was granted for this purpose (No. STUDY-26-00148). Informed consent was waived in this retrospective targeted chart review. The most common reasons for incompletion were associated with patient workup and care planning such as clinical instability, pending imaging/clearance, additional procedures or surgery, inability to tolerate simulation requiring anesthesia rescheduling, treatment plan changes, transfer to another facility, or patient preference changes. Hospice transition was not a predominant reason for simulation of non-completion in this cohort/time. Documentation compliance remained high throughout the study period, with averages of 96.95% [standard deviation (SD) 4.10%] and 97.83% (SD 3.77%), respectively. In our department, communication-related safety entries ranged from 0 to 3 per interval, peaking for 12 months and declining thereafter. All estimates are unadjusted, consistent with the observational study design.

Qualitative findings

Open-text completion for the analyzed fields was high across survey waves (6 months 11/11, 12 months 17/17, 18 months 18/19; 24 months 12/12 respondents provided a response to at least one of the free-text or workflow burden items). Open-ended responses to the APRT integration free-text prompts (what worked well and what did not work well) and additional free-text/workflow burden prompts (Mini-Z work stress how can it be improved, after-hours patient-care work, and common inpatient interruptions) were analyzed using inductive qualitative content analysis appropriate for brief free-text survey data. Responses were typically short (often one to a few sentences), so category percentages are reported descriptively to summarize what respondents most commented on at each interval.

Six content categories were identified: positive impact of APRT; administrative burden (work interruptions, workload control, and EMR efficiency); challenges with APRT (role clarity/workflow fit); inpatient coordination challenges; suggestions for improvement; and team dynamics. The positive impact of APRT was the dominant category at every interval, reported by 69.2% of respondents at 6 months and by more than 90% at 18–24 months. Early comments emphasized improved communication and help with inpatient coordination (e.g., “Very helpful in general, especially in coordinating with inpatient teams.”). By 24 months, comments reflected broader integration into day-to-day practice, including patient/family communication and workflow support (e.g., “I had more time to dedicate to my patients.” and “The APRT has simplified my life considerably. She helps with patient communication, scheduling, and bolus placement.”).

Administrative burden comments were also commonly referenced but were less frequent at later intervals over time (76.9% at 6 months to 53.8% at 24 months). Early comments focused on frequent interruptions and routine operational tasks (e.g., “Meetings.”). Calls from the machine for film checks. Mid-interval responses more often described ongoing communication demands tied to inpatient status changes and coordination (e.g., “Calls… that something about patient status has changed…calls about sim order approvals.”). By 24 months, fewer comments raised administrative burden, but persistent communication tasks were still noted (e.g., “Film review, patient calls.”).

Challenges with APRT decreased over time (38.5% at 6 months to 15.4% at 24 months) and largely reflected early uncertainty about role boundaries and workflow responsibilities, which improved as the role became established. Inpatient coordination challenges were not reported early but emerged at 12 and 18 months (20.8% and 21.1%), most often describing logistics across inpatient teams (e.g., “Logistics, coordinating with different teams on scheduling.”); these concerns declined by 24 months (7.7%). Suggestions for improvement were infrequent but increased modestly over time (0% to 15.4%) and tended to focus on practical ways to strengthen integration (e.g., “Wish there was a way for her to get automatically looped in with inpatient consults.”). Comments related to team dynamics were rare (≤7.7%) and did not indicate persistent concerns. Overall, the qualitative findings support increasing role integration over time, with consistent perceived benefit and fewer comments focused on role-fit issues, while acknowledging that some administrative and communication burdens remained.

Discussion

Over 24 months, APRT integration was associated with improved departmental QI/QA KPIs and lower clinician-reported burnout among respondents, with observed trends largely driven by attending ROs given the small number of respondents. Notably, our QI/QA operational performance data shows substantial temporal variation in inpatient demand (consults, simulations, discontinued PRT courses, and new inpatient visits), which are likely to translate into fluctuating documentation, messaging, and coordination that happens after hours. This operational context offers a plausible explanation for the observed peaks in EMR-related burden at 6 and 24 months, consistent with periods when clinicians may face higher cumulative EMR work driven by throughput and course complexity. Across the mid-study period, the pattern suggests that burnout drivers shifted over time—at 12 months the signal centered on documentation time, whereas by 18 months it aligned more with broader work system functioning (team efficiency, workload control, and perceived pace), consistent with dynamic operational pressures. Taken together, these patterns support a complex inpatient service in which burnout is expressed at times as EMR-centered and after-hours load and at others as loss of control, coordination strain, and accelerated pace, reflecting operational pressures suggesting ongoing system-level drivers that extend beyond the APRT’s scope and are supported in current literature (24-26). Free-text responses aligned with this pattern, describing stronger coordination and physician support while noting that some administrative and communication burdens remained. As such, the qualitative signal in the content analysis of comments demonstrates a shift from early interruptions and routine operational tasks toward later coordination and communication demands that remain structural and are not fully modifiable by these APRT intervention alone. These patterns are consistent with how the APRT role was designed to function in the inpatient workflow. The APRT’s structured coordination work—tracking simulation and treatment initiation readiness, identifying barriers (e.g., pending clearance/workup, transport needs, positioning tolerance, competing procedures), and communicating changes in real time—directly targets the processes most likely to influence simulation eligibility, simulation completion, and follow-through on the prescribed course.

By contrast, the APRT role does not replace physician documentation or EMR workload demands; therefore, it is expected that EMR-related strain and broader workplace stressors may persist even when throughput-related KPIs improve. Importantly, the model reinforces the attending RO’s role in clinical decision-making and oversight, with the APRT serving as an extension of the team to surface readiness issues early and support timely care delivery. Consistent with our prior inpatient throughput approach (2), these QI/QA KPIs are interpreted as service-level measures in a high-acuity setting and were contextualized with targeted chart review of postponements and non-completions. To our knowledge, there were no other department-led inpatient PRT workflow redesign initiatives implemented during the study intervals; however, we cannot exclude the influence of other unknown factors that could have confounded the results of this study.

Prior APRT evaluations in palliative and advanced practice settings have most often examined pathway efficiency using time-based endpoints (e.g., referral-to-consultation, consult-to-simulation, simulation-to-treatment) and process measures related to triage and coordination in predominantly outpatient workflows (4,16-18). In contrast, the current study evaluated an established APRT role in an inpatient service using QI/QA KPIs that reflect readiness and throughput, where postponements are frequently driven by medical instability, competing procedures, and evolving plans of care. International APRT models in contrast have reported benefits in care coordination, workflow efficiency, and continuity, particularly within palliative and adaptive radiotherapy services (16-19). These roles are structured to support time-sensitive, non-billable clinical tasks under physician supervision, enabling ROs to prioritize clinical decision-making and patient-facing care (16-19). The present findings are consistent with international APRT outcomes, but the U.S. inpatient PRT setting adds complexity because clinician responsibilities are tightly linked to reimbursement, quality expectations that continue to rise, and PRT programs are simultaneously expected to deliver cost conscious care (16-19,27). Importantly, our department does not have a dedicated advanced practice practitioner (e.g., nurse practitioner or physician assistant) to staff inpatient palliative RT consults. Thus, the logistical burdens traditionally have fallen onto the attending RO and/or residents. In our center, the APRT strengthened coordination and readiness for simulation and treatment while clinical decision-making, accountability, goals-of-care oversight, and all billable tasks remained with the attending RO.

The observed reduction in clinician burnout is particularly relevant when considered alongside national radiation oncology workforce data identifying documentation burden, after-hours work, and fragmented communication as key drivers of distress (7-9,24-26). While APRT integration in this current study did not eliminate these systemic stressors, improvements in perceived physician support and operational improvements suggest that advanced practice roles may mitigate these downstream effects. Qualitative findings reinforced this model, with clinicians describing communication, efficiency, and patient preparedness without erosion of physician oversight. As departments face increasing clinical complexity and workforce constraints, APRT integration may represent a scalable strategy to support time-sensitive inpatient workflows within clearly defined scope and governance frameworks (6,28). Recent international and national work on APRT preparation emphasizes that impact depends on standardized training, competency assessment, and clear supervision/decision boundaries (29). The APRT model in this study is consistent with the structured coordination and may help explain why improvements in inpatient KPIs coincided with perceived gains in physician support.

Limitations

This was a single-center study conducted in a busy academic tertiary-care hospital with a modest sample size; therefore, generalizability to other inpatient PRT programs, particularly smaller programs, should be interpreted cautiously. The observational design precludes causal inference, and all estimates are unadjusted because the study design did not support multivariable modeling. The survey was anonymous and did not collect identifiers, so individual responses could not be linked over time; each interval represents an independent cross-sectional sample rather than a longitudinal cohort. Variable response rates across timepoints may have introduced nonresponse bias, and self-reported measures may be subject to recall or social desirability bias. Resident responses may reflect different priorities than attendings, however the small number of resident respondents at each interval limited subgroup interpretation. Clinician well-being surveys were not collected prior to APRT integration; therefore, survey outcomes could not be compared with a true pre-implementation control period, and the 0–6-month interval represents an early integration reference period rather than a true control. Inpatient case-mix and referral patterns may have varied over time (including performance status, acuity, and goals of care), which could influence operational metrics independent of APRT integration. Accordingly, simulation eligibility, simulation completion, and treatment completion are presented as operational, service-level metrics and should not be interpreted as patient-level causal evidence. Because this was an anonymous, repeated cross-sectional study with variable response rates, these observed trends should be interpreted cautiously as associative and hypothesis-generating.

Future directions

Future multi-institutional studies and comparisons across health systems are needed to assess generalizability, define standardized practices, and further clarify the role of APRTs within U.S. radiation oncology care models. Results suggest that APRT integration may offer a feasible strategy to improve departmental performance in key performance areas and reduce specific contributors to clinician burden in inpatient PRT settings. Future research should also evaluate strategies such as documentation streamlining and workload distribution to optimize the model and support long-term clinician wellness, with outcomes assessed separately for attending physicians and trainees and with study designs that allow more robust longitudinal assessment.

Conclusions

The integration of an APRT into an inpatient PRT service was associated with improvements in workflow efficiency, including higher simulation eligibility and greater full-course treatment completion. Clinician-reported burnout also decreased among survey respondents over the 24-month follow-up period; however, given the anonymous repeated cross-sectional design and varying response rates across timepoints, burnout findings should be interpreted as exploratory and hypothesis-generating rather than confirmatory. Persistent stressors—particularly documentation burden, after-hours communication, and workload intensity—remained unchanged, underscoring structural challenges that extend beyond the APRT’s responsibilities and reaffirm the indispensable role of ROs as primary medical providers in inpatient PRT. Furthermore, drawing from these findings, the research team—working with physicians and system leadership—identified that the APRT model may allow physicians to focus more consistently on higher-level clinical decision-making and other physician-led responsibilities by safely offloading time-sensitive, non-billable coordination tasks within a defined scope and clinical guardrails. As the model continues to be refined, the APRT role may be extended to other complex patient populations and workflows where clinician time and presence in non-billable capacities can be safely supplemented by an appropriately trained APRT. Two workflows under consideration within this current system include Magnetic Resonance Imaging Guided Linear Accelerator (MR-Linac) adaptive radiotherapy and brachytherapy services across the health system.

Acknowledgments

The authors used ChatGPT (OpenAI) and Grammarly to assist with enhancing clarity and flow/editing for grammar and style.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://apm.amegroups.com/article/view/10.21037/apm-2025-1-144/rc

Data Sharing Statement: Available at https://apm.amegroups.com/article/view/10.21037/apm-2025-1-144/dss

Peer Review File: Available at https://apm.amegroups.com/article/view/10.21037/apm-2025-1-144/prf

Funding: This work was supported by the Icahn School of Medicine at Mount Sinai’s Office of Well-being and Resilience.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://apm.amegroups.com/article/view/10.21037/apm-2025-1-144/coif). D.M. reports departmental support for Annals of Palliative Medicine publication fees, ASTRO 2025 conference attendance and abstract presentation, and an unpaid leadership role as Chair of the RTANYS Advocacy Committee. K.G. discloses paid advisory board roles with RenovoRX, GSK, and Agenus, as well as an unpaid leadership position on the Board of Directors of the American Society of Clinical Oncology. K.D. reports project support from the Mount Sinai OWBR REDUCE Award and NIA K76AG068516-01A1 (Paul Beeson Career Development Award), as well as book royalties from Elsevier. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This study was approved by the Icahn School of Medicine Institutional Review Board 04/28/2023 (No. Study-23-00265). Participants were informed of the study before accessing the survey. An additional Icahn School of Medicine Institutional Review Board approval was granted for retrospective targeted chart review (No. STUDY-26-00148). Informed consent was waived in this retrospective targeted chart review.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Marshall DC, Dharmarajan K, Wei R, et al. Key factors for establishing and sustaining a successful palliative radiation oncology program: a survey of the Society for Palliative Radiation Oncology. Ann Palliat Med 2024;13:754-65. [Crossref] [PubMed]
2. McDonagh D, Starrs C, Skubish S, et al. Effect of an Advanced Practice Radiation Therapist Intervention on Inpatient Radiation Therapy Throughput. Radiation Therapist 2025;34:14.
3. Caldwell S, Lee S. Defining Advanced Practice Radiation Therapy at The University of Texas MD Anderson Cancer Center. Radiation Therapist 2025;34:32-40.
4. Beckert R, Schiff JP, Morris E, et al. The impact of an Advanced Practice Radiation Therapist contouring for a CBCT-based adaptive radiotherapy program. Tech Innov Patient Support Radiat Oncol 2024;30:100242. [Crossref] [PubMed]
5. Clarkson M, Dimopoulos M. Incorporating the 4 Pillars of Advanced Practice in the APRT Role in the United States. Radiation Therapist 2025;34:80-87.
6. Consensus Committee on the Future of Medical Imaging and Radiation Therapy. White Paper From the 2024 Consensus Committee on the Future of Medical Imaging and Radiation Therapy. American Society of Radiologic Technologists; 2024. Available online: https://www.asrt.org/docs/default-source/research/whitepapers/2024-consensus-committee-on-the-future-of-medical-imaging-and-radiation-therapy.pdf?sfvrsn=1f869819_12
7. Garner D, Koong AC, Martel MK, et al. Burnout among Radiation Oncology Providers and Staff in a Large Academic Center. Int J Radiat Oncol Biol Phys 2020;108:S123. [Crossref]
8. Hoffman KE, Garner D, Koong AC, et al. Understanding the intersection of working from home and burnout to optimize post-COVID-19 work arrangements in radiation oncology. Int J Radiat Oncol Biol Phys 2020;108:370-373. [Crossref] [PubMed]
9. Franco P, Tesio V, Bertholet J, et al. Professional quality of life and burnout amongst radiation oncologists: The impact of alexithymia and empathy. Radiother Oncol 2020;147:162-8. [Crossref] [PubMed]
10. Department of Radiation Oncology. QA Work Product – M&M: Unfinished Radiation Therapy Courses. January–September 2021. Mount Sinai Hospital; 2021. [dataset] Department of Radiation Oncology; 2021; Unfinished RT Courses dataset; Mount Sinai Hospital repository; Version 1.
11. Dharmarajan K. Improving care of advanced cancer patients with a dedicated palliative radiotherapy team. Oncology Issues 2019;34:28-33. [Crossref]
12. Allred PA, Polansky MN, Doerksen K, et al. Advanced Practitioners: Collaborators in Radiation Oncology. J Adv Pract Oncol 2019;10:873-7. [PubMed]
13. Martin KL, Krechmer B, Boyajian RN, et al. Advanced Practice Providers in Radiation Oncology. Pract Radiat Oncol 2020;10:e192-8. [Crossref] [PubMed]
14. Chan K, Chan B, Linden K, et al. Framework Development: Standardizing Definition of Advanced Practice Radiation Therapy Activities for Clinical Workload Quantification. Tech Innov Patient Support Radiat Oncol 2024;29:100238. [Crossref] [PubMed]
15. Lawlor S, Leech M. Established advanced practice roles in radiation therapy: A scoping review. J Med Imaging Radiat Oncol 2024;68:342-52. [Crossref] [PubMed]
16. Roos D, Job M, Holt T. Establishing a palliative Advanced Practice Radiation Therapist role: A viable alternative to a Rapid Access Palliative Radiation Therapy clinic in Australia. J Med Imaging Radiat Oncol 2022;66:117-28. [Crossref] [PubMed]
17. Job M, Holt T, Bernard A. An evaluation of an advanced practice role in palliative radiation therapy. J Med Radiat Sci 2019;66:96-102. [Crossref] [PubMed]
18. Rozanec N, Lavergne C, Harnett N. A Canadian experience of palliative advanced practice radiation therapy TIPS: Training, implementation, practice and sustainability. Tech Innov Patient Support Radiat Oncol 2021;17:89-96. [Crossref] [PubMed]
19. Koh CY, Loh YNY, Cheo STT. Establishing the Introduction of Advanced Practice Radiation Therapist (APRT) in Palliative Radiation Therapy – Experience of A Single Oncology Centre. Radiography 2025;31:103069. [Crossref]
20. Dolan ED, Mohr D, Lempa M, et al. Using a single item to measure burnout in primary care staff: a psychometric evaluation. J Gen Intern Med 2015;30:582-7. [Crossref] [PubMed]
21. Khanna N, Montgomery R, Klyushnenkova E. Joy in Work for Clinicians and Staff: Identifying Remedial Predictors of Burnout from the Mini Z Survey. J Am Board Fam Med 2020;33:357-67. [Crossref] [PubMed]
22. Elo S, Kyngäs H. The qualitative content analysis process. J Adv Nurs 2008;62:107-15. [Crossref] [PubMed]
23. Hsieh HF, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res 2005;15:1277-88. [Crossref] [PubMed]
24. Goldman DA, Panageas KS. Electronic Medical Record Documentation and Provider Burnout. JCO Oncol Pract 2021;17:158-9. [Crossref] [PubMed]
25. Holmgren AJ, Apathy NC, Crews J, et al. National trends in oncology specialists' EHR inbox work, 2019-2022. J Natl Cancer Inst 2025;117:1253-1259. [Crossref] [PubMed]
26. Beltràn Ponce S, Small CJ, Amini A, et al. Overcoming Burnout and Promoting Wellness in Radiation Oncology: A Report From the ACR Commission on Radiation Oncology. J Am Coll Radiol 2023;20:487-93. [Crossref] [PubMed]
27. Bruggeman AR, Robbins JR, Chang EM, et al. Palliative radiation oncology programs: improving value through high-quality and cost-effective care. Ann Palliat Med 2025;14:247-54. [Crossref] [PubMed]
28. Skubish S, Caldwell S, Hayden S, et al. The Current and Future State of Radiation Therapy Practice—An Analysis of the Professional Workforce Survey. Practical Radiation Oncology 2025;15:e511-e518. [Crossref] [PubMed]
29. Tsang Y, Skubish S, Dimopoulos M, et al. Gathering evidence on preparation for advanced practice in radiation therapy: An international focus group synthesis. Tech Innov Patient Support Radiat Oncol 2025;36:100361. [Crossref] [PubMed]